We propose NeuMIP, a neural method for representing and rendering a variety of material appearances at different scales. In this work, we generalize traditional mipmap pyramids to pyramids of neural textures, combined with a fully connected network. We also introduce neural offsets, a novel method which allows rendering materials with intricate parallax effects without any tessellation. Neural materials within our system support a 7-dimensional query, including position, incoming and outgoing direction, and the desired filter kernel size. The materials have small storage, and can be integrated within common Monte-Carlo path tracing systems.

2021: Alexandr Kuznetsov, Krishna Mullia, Zexiang Xu, Milos Hasan, R. Ramamoorthi

Keywords: Graphics, Machine Learning, Image and Video Processing

https://arxiv.org/pdf/2104.02789.pdf